Dynamic exchange method and apparatus

ABSTRACT

In a live, expressive combinatorial exchange, each of a plurality of bidders can submit a bid. Based on the submitted bids, an allocation of the bids is determined that is optimal for the type of exchange being conducted. At least a portion of each bid of the allocation is displayed to each bidder of a first subset of the bidders that has at least one bid that is not included in the allocation. Each bidder of a subset of the first subset of bidders can then amend one or more of their existing bids or submit a new bid that is considered the next time the allocation is determined. The process of feeding back at least a portion of each bid of the allocation, submitting new bids or amendments to existing bids, and determining a new allocation based on all of the submitted bids continues until a predetermined condition is satisfied.

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application is a continuation-in-part of U.S. patentapplication Ser. No. 10/254,241, filed Sep. 25, 2002, which isincorporated herein by reference.

BACKGROUND OF THE INVENTION

[0002] 1. Field of the Invention

[0003] The present invention relates to combinatorial exchanges and,more particularly, to a method of conducting a live, expressivecombinatorial exchange, and computer instructions which, when executedby a processor, cause the processor to perform one or more steps of themethod.

[0004] 2. Description of Related Art

[0005] Various systems have been proposed and constructed to supportonline exchanges. The most general type of exchange is a pure exchangewhich permits one or more bidders to offer to sell and/or purchase oneor more items to/from one or more bid takers. An item may be any entityof value, such as a good, service or money. A forward auction is aspecial case of an exchange with a single seller. A reverse auction is aspecial case of an exchange with a single buyer.

[0006] Combinatorial exchanges support advanced exchange designs andexpressive bidding. These features permit the exchange to be designed toachieve best economic efficiency.

[0007] One example of expressive bidding is combinatorial bids.Combinatorial bids allow bidders to bid on multiple items with a singlebid. The combination, or bundle of items, is determined by the bidder.This is advantageous when the items exhibit complementarity, i.e., whenthe value of the bundle of items is worth more to the bidder than thesum of the separate item values, or substitutability, i.e., wheredifferent items are interchangeable to the bidder. Combinatorial bidsallow bidders to express their true preference, resulting in the besteconomic allocation.

[0008] Heretofore, participants in a combinatorial exchange, especiallybidders and bid takers, received little or no meaningful feedbackregarding submitted bids and/or rules that determine how the exchangeallocation is determined. This lack of meaningful feedback oftenresulted in bidders placing bids without any assurance that such bid(s)would be competitive. While simple forward or reverse auctions oftenprovide feedback regarding the current winning price, in a combinatorialexchange, especially a live exchange, providing the current winningprice may be, and often is, insufficient to enable exchange participantsto submit competitive bids and/or rules that modify the exchangeobjective. This is because the current winning price is often not theonly criteria by which an allocation is determined in a combinatorialexchange.

[0009] What is, therefore, needed and not disclosed in the prior art isa method and apparatus for conducting a live combinatorial exchange thatovercomes the above problem and others.

SUMMARY OF THE INVENTION

[0010] The invention is a method of conducting a live combinatorialexchange. The method can include (a) receiving from each of a pluralityof bidders at least one bid comprised of at least one item, an initialquantity of each item, and a price for all of the item(s) and theirquantities; (b) determining an allocation that is optimal for the typeof exchange being conducted, wherein said allocation includes aplurality of bids with each bid of said allocation including all of theitems of the bid and at least part of the initial quantity of each item;(c) causing at least a portion of each bid of said allocation to bedisplayed to each bidder a first subset of the bidders that has at leastone bid that is not included in said allocation; (d) receiving from eachbidder of a subset of the first subset of bidders at least one of a newbid and an amendment to an existing bid of the bidder; and (e) repeatingsteps (b)-(d) until a predetermined condition is fulfilled.

[0011] Each item can include one of a tangible good, a service andmoney.

[0012] The predetermined condition can include (i) a lapse of apredetermined time interval from commencement of the exchange, (ii) amanual abort, or (iii) a sum of the prices of the bids of the allocationreaching a predetermined value.

[0013] Each bid of a subset of the bids can have associated therewithexchange description data (EDD) established by the bidder of said bid(bidder EDD). Bidder EDD can include at least one rule (or constraint)for processing (i) a bid, (ii) at least one item of a bid, and/or (iii)a subset of bids that includes all or less than all of the bids whendetermining the allocation. Step (b) can further include determining theallocation as a function of bidder EDD.

[0014] Bidder EDD can include at least one rule related to: bidattribute(s), bid adjustment(s), item attribute(s), item adjustment(s),free disposal, action, cost constraint/requirement, unitconstraint/requirement, counting constraint/requirement, homogeneityconstraint, mixture constraint, cost/unit condition pricing, quoterequest and reserve price(s).

[0015] The portion of the at least one bid in step (c) can include (i)the at least one item of the bid, (ii) the quantity of the at least oneitem of the bid, (iii) the price for all of item(s) and theirquantities, and/or (iv) at least a portion of the bidder EDD.

[0016] The method can further include displaying a portion of at leastone bid that was determined to be part of the allocation to each bidderof a second subset of bidders that has at least one bid that is part ofthe allocation.

[0017] Each subset of bidders can include all or less than all of thebidders, and each subset of bids can include all or less than all of thebids.

[0018] The exchange can be a pure exchange, a forward auction or areverse auction.

[0019] The amendment to the existing bid in step (d) can include theaddition of at least one new rule to bidder EDD associated with theexisting bid; the deletion of at least one rule from bidder EDDassociated with the existing bid; the amendment of a value associatedwith at least one rule of bidder EDD associated with the existing bid;the amendment of a value of the quantity of at least one item of theexisting bid; and/or the amendment of the price for all of the item(s)and their quantities.

[0020] The method can further include imposing at least one supervisoryconstraint that limits at least one of (i) adding at least one rule to abidder EDD, (ii) deleting at least one rule from a bidder EDD, (iii)relaxing at least one rule of a bidder EDD and (iv) tightening at leastone rule of a bidder EDD.

[0021] Step (b) can further include determining the allocation based onEDD established by a bid taker (bid taker EDD). Step (d) can furtherinclude receiving from the bid taker a new bid taker EDD and/or anamendment to an existing bid taker EDD of the bid taker. The amendmentto the existing bid taker EDD of the bid taker can include adding atleast one new rule to the existing bid taker EDD; deleting at least onerule from the existing bid taker EDD; and/or amending a value associatedwith at least one rule of the existing bid taker EDD.

[0022] The method can further include extending the predetermined timeinterval in response to receiving a bid that improves the allocationwithin a predetermined duration of the end of the predetermined timeinterval. In an exchange that includes plural bidders and plural bidtakers, the allocation improves if (i) the number of items exchangedincreases or (ii) if a difference between a sum of the prices of the buybids and a sum of the prices of the sell bids of the allocationincreases. In an exchange that includes plural buyers and a singleseller, i.e., a forward auction, the allocation improves if a sum of theprices of the bids of the allocation increases. In an exchange thatincludes a single buyer and plural sellers, i.e., a reverse auction, theallocation improves if a sum of the prices of the bids of the allocationdecreases.

[0023] The method can further include OR'ing all the received bids andXOR'ing bids received from one bidder that include at least one item incommon.

[0024] Step (b) can further include determining the allocation as afunction of exchange description data (EDD) established by a bid taker(bid taker EDD). Bid taker EDD can include at least one rule (orconstraint) for processing a bid, at least one item of a bid, and/or asubset of the plurality of the bids when determining the allocation.

[0025] Step (d) can further include receiving from the bid taker atleast one of new bid taker EDD and an amendment to an existing bid takerEDD of the bid taker. The amendment to the existing bid taker EDD of thebid taker can include adding at least one new rule to the existing bidtaker EDD, deleting at least one rule from the existing bid taker EDD,and/or amending a value associated with at least one rule of theexisting bid taker EDD.

[0026] The method can further include imposing at least one supervisoryconstraint that limits at least one of (i) adding at least one rule to abid taker EDD, (ii) deleting at least one rule from a bid taker EDD,(iii) relaxing at least one rule of a bid taker EDD and (iv) tighteningat least one rule of a bid taker EDD.

[0027] The bid taker EDD can include at least one rule related to:objective(s), constraint relaxer(s), feasibility obtainer(s), bidadjustment(s), item attribute(s), item adjustment(s), free disposal,action, cost constraint/requirement, unit constraint/requirement,counting constraint/requirement, homogeneity constraint, mixtureconstraint, cost/unit condition pricing, quote request and reserveprice(s).

[0028] The method can further include causing an identification of thebidder of the bid to be displayed in step (c). The displayed bidderidentification can be obscured.

[0029] At least one rule can be introduced into at least one bidder EDDin response to a bidder specifying (i) a precondition of said rule and(ii) an effect to be applied if said precondition is satisfied. At leastone rule can be introduced into at least one bid taker EDD in responseto a bid taker specifying (i) a precondition of said rule and (ii) aneffect to be applied if said precondition is satisfied. The bidderand/or the bid taker can utilize a graphical user interface on a display18 of a computer 2 to specify the precondition and the effect.

[0030] Any one or combination of the foregoing steps can be embodied oncomputer readable medium as instructions which, when executed by aprocessor, cause the processor to perform one or more of said steps.

BRIEF DESCRIPTION OF THE DRAWINGS

[0031]FIG. 1 is a block diagram of an exemplary computer that can beutilized by each participant in a live, expressive combinatorialexchange;

[0032]FIG. 2 is a generalized block diagram of networked participants inthe live, expressive combinatorial exchange, wherein each participantutilizes a computer of the type shown in FIG. 1 to participate in theexchange;

[0033]FIG. 3 is block diagram of exemplary bid having bidder exchangedescription data (EDD) associated therewith;

[0034]FIG. 4 is a block diagram of bid taker EDD;

[0035]FIG. 5 is a block diagram of a bid having associated therewithbidder EDD that has rules associated therewith related to free disposal,reserve price, action, item attribute and item adjustment;

[0036]FIGS. 6a and 6 b are a block diagram of a bid and an associatedbidder EDD that has rules associated therewith related to bid attributesand bid adjustments;

[0037]FIG. 7a is a block diagram of a bid and an associated bidder EDDthat has a cost constraint rule associated therewith;

[0038]FIG. 7b is a block diagram of a bid and an associated bidder EDDthat has a cost requirement rule associated therewith;

[0039]FIG. 8a is a block diagram of a bid and an associated bidder EDDthat has a unit constraint rule associated therewith;

[0040]FIG. 8b is a block diagram of a bid and an associated bidder EDDthat has a unit requirement rule associated therewith;

[0041]FIG. 9a is a block diagram of a bid and an associated bidder EDDthat has a counting constraint rule associated therewith;

[0042]FIG. 9b is a block diagram of a bid and an associated bidder EDDthat has a counting requirement rule associated therewith;

[0043]FIG. 10 is a block diagram of a bid and an associated bidder EDDthat has a homogeneity rule associated therewith;

[0044]FIG. 11 is a block diagram of a bid and an associated bidder EDDthat has a mixture constraint rule associated therewith;

[0045]FIG. 12 is a block diagram of a bid and an associated bidder EDDthat has a cost conditional pricing rule associated therewith;

[0046]FIG. 13 is a block diagram of a bid and an associated bidder EDDthat has a unit conditional pricing rule associated therewith;

[0047]FIG. 14 is a block diagram of a bid taker EDD that has anobjective rule associated therewith;

[0048]FIG. 15 is a block diagram of a bid taker EDD that has aconstraint relaxer rule associated therewith;

[0049]FIG. 16 illustrates the various allocations resulting from theselection of corresponding desired solutions of the constraint relaxerrule of FIG. 15; and

[0050]FIG. 17 is a flowchart of a method of conducting a live,expressive combinatorial exchange in accordance with the presentinvention.

DETAILED DESCRIPTION OF THE INVENTION

[0051] The present invention is directed to a method for solving a live,expressive combinatorial exchange.

[0052] With reference to FIG. 1, the present invention is embodied incomputer software which executes on one or more networked computers 2.Each computer 2 includes a microprocessor 4, a computer storage 6 and aninput/output system 8. Each computer 2 can also include a media drive10, such as a disk drive, CD-ROM drive, and the like. Media drive 10 canoperate with a computer storage medium 12 capable of storing thecomputer software that embodies the present invention, which computersoftware is able to configure and operate computer 2 in a manner toimplement the present invention. Input/output system 8 can include akeyboard 14, a mouse 16 and/or a display 18. Computer 2 is exemplary ofa computer capable of executing the computer software of the presentinvention and is not to be construed as limiting the invention.

[0053] With reference to FIG. 2, and with continuing reference to FIG.1, a typical exchange includes a plurality of bidders 22, an exchangemanager 24 and a plurality of bid takers 26. Each bidder 22, theexchange manager 24 and each bid taker 26 utilizes a computer 2 of thetype described above to conduct the auction. The computer 2 of exchangemanager 24 is networked to the computers 2 of bidders 22 and thecomputers 2 of bid takers 26. The computer 2 of exchange manager 24includes optimizing software that is utilized to process bids receivedfrom bidders 22, and/or rules associated with “exchange descriptiondata” (EDD) accompanying one or more bids received from bidders 22and/or received from one or more bid takers 26. The EDD received frombidders 22 and/or bid takers 26 modifies the manner in which theoptimizing software determines a feasible solution or allocation that isoptimal for the type of exchange being conducted. Examples of the typesof exchanges that can be conducted include a pure exchange having pluralbidders and plural bid takers that exchange items such as tangiblegoods, services and/or money; an exchange having plural buyers and asingle seller (forward auction); and an exchange that includes a singlebuyer and plural sellers (reverse auction). However, this is not to beconstrued as limiting the invention.

[0054] One example of optimizing software includes a linear or mixedinteger program solver that includes one or more decision variables eachhaving one or more associated bounds or constraints. Another example ofoptimizing software suitable for use with the present invention isdescribed in U.S. Pat. No. 6,272,473 which is incorporated herein byreference. In operation, the optimizing software determines an optimalsolution or allocation for the type of exchange being conducted subjectto bids received from bidders 22, EDD associated with the one or morebids received from bidders 22, and/or EDD received from one or more bidtakers 26.

[0055] With reference to FIG. 3, and with continuing reference to FIGS.1 and 2, during an exchange event, each bidder 22 can provide toexchange manager 24 one or more bids 50 that can include one or moreitems I1 52-1, I2 52-2, I3 52-3, . . ., IN 52-N having associatedquantities 54-1, 54-2, 54-3, . . ., 54-N, respectively, and anassociated bid price 56. Each bid 50 can also have associated therewithbidder EDD 58.

[0056] Each bidder EDD 58 can include data that a preprocessor ofcomputer 2 of exchange manager 24 converts into one or more rules forprocessing by the optimization software to determine the optimalallocation of bids. Also or alternatively, each bidder EDD 58 can haveassociated therewith one or more rules for processing by theoptimization software to determine the optimal allocation of bids. Eachrule associated with a bidder EDD 58 is typically derived from dataentered into fields displayed on a display of the computer 2 of thebidder 22 submitting the bid. However, this is not to be construed aslimiting the invention since the rules associated with a bidder EDD 58may also be derived from data entered into the computer 2 of exchangemanager 24 and/or data entered into the computer 2 of one or more bidtakers 26.

[0057] With reference to FIG. 4, and with continuing reference to FIGS.1-3, each bid taker 26 can provide to computer 2 of exchange manager 24one or more bid taker EDD 60, each of which has one or more rulesassociated therewith, that the optimizing software utilizes to determinethe optimal allocation of bids received from bidders 22. Like the rulesassociated with each bidder EDD 58, the rules associated with each bidtaker EDD 60 can be instantiated at the computer 2 of the correspondingbid taker 26 in response to the entry of corresponding data by bid taker26, or by the preprocessor of the computer 2 of exchange manager 24 fromdata extracted from the bid taker EDD 60 received from the correspondingbid taker 26. Each rule associated with a bid taker EDD 60 is typicallyderived from data entered into fields displayed on a display of thecomputer 2 of the bid taker 26 submitting the bid taker EDD 60. However,this is not to be construed as limiting the invention since the rulesassociated with a bid taker EDD 60 may also be derived from data enteredinto the computer 2 of exchange manager 24 and/or data entered into thecomputer 2 of one or more bidders 22.

[0058] As can be seen, each bidder EDD 58 and/or each bid taker EDD 60includes one or more rules that the optimizing software utilizes todetermine the optimal allocation, and/or includes data that apreprocessor of the computer 2 of the exchange manager converts into oneor more rules that the optimizing software utilizes to determine theoptimal allocation. For the purpose of simplifying the description ofthe invention, hereinafter, each bidder EDD 58 and each bid taker EDD 60will be described as having one or more rules associated therewithwithout regard to where said one or more rules were instantiated.

[0059] Each bidder EDD 58 has associated therewith at least one rulerelated to bid attribute(s), bid adjustment(s), item attribute(s), itemadjustment(s), free disposal, action, cost constraint/requirement, unitconstraint/requirement, counting constraint/requirement, homogeneityconstraint, mixture constraint, cost/unit condition pricing, quoterequest and reserve price(s). Each bid taker EDD 60 has associatedtherewith at least one rule related to objective(s), constraintrelaxer(s), feasibility obtainer(s) bid adjustment(s), itemattribute(s), item adjustment(s), free disposal, action, costconstraint/requirement, unit constraint/requirement, countingconstraint/requirement, homogeneity constraint, mixture constraint,cost/unit condition pricing, quote request and reserve price(s). Theserules will now be described in greater detail.

[0060] With reference to FIG. 5, and with continuing reference to FIGS.1-4, suppose that bid 50 only includes item I1 52-1 for a quantity 54-1of 10 at a price 56 of $10.00. If bid 50 is created by a bidder 22acting as a buyer, price 56 indicates the amount bidder 22 is willing topay (or “bid”) for the quantity 54-1 of item 52-1. In contrast, if bid50 is created by a bidder 22 acting as a seller, price 56 is an amountbidder 22 would like to receive (or “ask”) for the quantity 54-1 of theitem 52-1. If desired, bid 50 can be for a plurality of items 52, eachof which has its own associated quantity, and price 56 can be for all ofthe quantities of all of the items. In FIG. 5, bid 50 has associatedtherewith a bidder EDD 58 that has associated therewith one or morerules related to free disposal 70, reserve price 72 and/or action 74.

[0061] Free Disposal Rule:

[0062] When a bidder 22 acts as a seller, a bidder EDD 58 associatedwith a bid 50 of bidder 22 can have associated therewith a free disposalrule 70 that enables the optimizing software to sell less than thespecified quantity 54-1 of item 52-1 without affecting bid price 56.When bidder 22 is acting as a buyer, the free disposal rule 70 enablesthe optimizing software to accept more than the specified quantity 54-1of item 52-1 without affecting the bid price 56: The free disposal rule70 may be used on both the supply side and demand side of all exchangeformats, including forward auctions and reverse auctions. In the exampleof bid 50 shown in FIG. 5, bidder 22 acting as a seller offering aquantity 54-1 of 10 units of item 52-1 for sale causes the free disposalrule 70 to be associated with bidder EDD 58 of bid 50, and causes aquantity of 5 to be associated with the free disposal rule 70. Theassociation of this quantity with the free disposal rule 70 informs theoptimizing software that bidder 22 acting as a seller is willing to sellbetween 5 and 10 units of item I1 52-1 for bid price 56.

[0063] Also or alternatively, free disposal rule 70 can be associatedwith a bid taker EDD 60 of a bid taker 26. The association of thequantity of 5 with the free disposal rule 70 associated with a bid takerEDD 60 informs the optimizing software that the bid taker acting as aseller or buyer is willing to sell or buy between 5 and 10 units of itemI1 52-1 for bid price 56.

[0064] Reserve Price Rule (for Bidder):

[0065] Bidder EDD 58 can also or alternatively have associated therewitha reserve price rule 72 that has a corresponding reserve priceassociated therewith. The reserve price associated with reserve pricerule 72 informs the optimizing software the maximum price above whichbidder 22 acting as a buyer will not buy item 5-1, or a minimum pricebelow which bidder 22 acting as a seller will not sell item 52-1. Inbidder EDD 58, a reserve price of $7 is associated with reserve pricerule 72. This indicates that bidder 22 acting as a seller or a buyerdoes not wish to sell or buy any quantity of item 52-1 at a price belowor above, respectively, $7.

[0066] Also or alternatively, a bid taker EDD can have associatedtherewith a reserve price rule that causes the optimizing software toset the maximum or minimum price the corresponding bid taker is willingto receive or pay for a quantity of an item of a bid.

[0067] Action Rule:

[0068] Bidder EDD 58 can also or alternatively have associated therewithan action rule 74 that the bidder 22 of the corresponding bid 50 can seteither to buy or sell. In a forward auction or exchange, setting actionrule 74 to “sell” informs the optimizing software that bidder 22 isacting as a seller and item I1 52-1 is being sold. In a reverse auctionor exchange, setting action rule 74 to “buy” informs the optimizingsoftware that bidder 22 is acting as a buyer and item I1 52-1 is beingbought. In FIG. 5, action rule 74 is set to buy, indicating that bidder22 wishes to purchase the quantity 54-1 of ten of item I1 52-1. However,if action rule 74 is set to sell, the quantity 54-1 of ten associatedwith bid 50 specifies the total number of units of item I1 52-1 thatbidder 22 wishes to sell.

[0069] Similarly, a bid taker EDD 60 can also or alternatively haveassociated therewith an action rule, like action rule 74, that informsthe optimizing software that the bid taker 26 is acting as a buyer or aseller.

[0070] Item Attribute Rule:

[0071] Bidder EDD 58 can also or alternatively have associated therewithone or more item attribute rules 78 that the optimizing softwareutilizes to complete or refine the specification for each item 52 of bid50. For example, bidder EDD 58 can have associated therewith an itemattribute field color rule 78-1, a weight rule 78-2 and/or city rule78-3 for item 52-1. Bid 50 includes a plurality of items 52, each ofwhich can share one or more item attribute rules 78 and/or can have oneor more item attribute rules 78 associated uniquely therewith.

[0072] In FIG. 5, item attribute rule 78-1 informs the optimizingsoftware that the only acceptable colors for each unit of item I1 52-1are red, green and blue. Item attribute weight rule 78-2 informs theoptimizing software that the minimum and maximum acceptable weights foreach unit of item I1 52-1 are 10 kg and 14 kg, respectively. Itemattribute city rule 78-3 informs the optimizing software the name of thecity where item I1 52-1 is to be shipped from. Other item attributerules associated with bidder EDD 58 can include width, height, purity,concentration, pH, brand, hue, intensity, saturation, shade,reflectance, origin, destination, volume, earliest pickup time, latestpickup time, earliest drop-off time, latest drop-off time, productionfacility, packaging and flexibility.

[0073] In response to receiving bid 50 having associated therewithbidder EDD 58 with action rule 74 is set to “buy”, if a sell bid isreceived that specifies a color not listed in item attribute color rule78-1, a weight outside the range listed in item attribute weight rule78-2 or a city not listed in item attribute city rule 78-3, theoptimizing software will not include the sell bid in the allocation.Otherwise, the bid shown in FIG. 5 will be processed by the optimizingsoftware when determining the allocation.

[0074] Similarly, a bid taker EDD 60 can also or alternatively haveassociated therewith one or more item attribute rules, like itemattribute rules 78, that inform the optimizing software that thecorresponding bid taker 26 acting as a seller or a buyer is willing tosell or buy only items having the item attributes listed in acorresponding item attribute rule.

[0075] Item Adjustment Rule(s):

[0076] Bidder EDD 58 can also or alternatively have associated therewithone or more item adjustment value rules 84 that the optimizing softwareutilizes to process bid 50. Each item adjustment value rule 84 includesa condition and value whereupon, if the condition is valid, then thevalue is applied to the bid. For example, bidder EDD 58 can haveassociated therewith item adjustment value rules 84-1 and 84-2. Itemadjustment value rule 84-1 informs the optimizing software that a valueof $2 should be applied to a bid 50 for each unit of a green coloreditem I1 52-1. Item adjustment value field 84-2 informs the optimizingsoftware that a value of $1 should be applied to a bid 50 for each unitof item 54-1 that has a weight greater than or equal to 11.0 kg.

[0077] Bid taker EDD 60 can also or alternatively have associatedtherewith one or more item adjustment value rules, like item adjustmentvalue rule 84, that inform the optimizing software that thecorresponding bid taker is willing to adjust a value paid for orreceived by the bid taker if a condition associated with each itemadjustment value rule is satisfied.

[0078] As can be seen, the free disposal, reserve price, action, itemattribute(s) and item adjustment(s) rules of bidder EDD 58 and/or bidtaker EDD 60 operate on one or more items of a bid 50. However, it mayalso or alternatively be desirable for bidder EDD 58 and/or bid takerEDD 60 to have associated therewith rules that operate on a bid 50 as awhole versus one or more items of bid 50. Two types of rules thatoperate on a bid as a whole are bid attribute rule(s), which are usedwith bidder EDD 50, and bid adjustment rule(s), which can be used withbidder EDD 58 and/or bid taker EDD 60. These rules will now bedescribed.

[0079] With reference to FIGS. 6a-6 b, and with continuing reference toFIGS. 1-5, bidder EDD 58 can also or alternatively have associatedtherewith one or more bid attribute rules 92 and/or one or more bidadjustment rules 100 that quantify the effects of non-priceattribute(s), e.g., item attribute(s), discussed above, and bidattribute(s), discussed hereinafter, on the determination of whether bid50 is satisfied. These attribute(s) can be properties that allowincomplete item specification and, therefore, more economicallyefficient and participant-friendly market places. Any measurable,quantifiable or qualitative attribute can be defined to determine theparameters and character of the exchange.

[0080] Bid Attribute Rule:

[0081] Exemplary bid attribute rules 92 include a credit worthiness rule92-1, a bidder location rule 92-2 and a shipping cost rule 92-3. In FIG.6a, credit worthiness rule 92-1 includes three selections 104-1-104-3 bywhich a bid 50 can be set to a level of credit worthiness of the bidder.The selection of the credit worthiness “Poor” 104-1 informs theoptimizing software that the bidder 22 of bid 50 has bad credit.Likewise, the selection of the credit worthiness “Good” or “Excellent”104-2 or 104-3 informs the optimizing software that the bidder 22 of bid50 has good or excellent credit. To avoid falsification of creditworthiness, the selection of a credit worthiness 104 associated withcredit worthiness rule 92-1 is typically made by exchange manager 24.However, this is not to be construed as limiting the invention.

[0082] Location rule 92-2 can have associated therewith data, in theform of an alphanumeric string, that informs the optimizing softwarewhere the bidder of bid 50 resides. Shipping cost rule 92-3 can haveassociated therewith data, in the form of a decimal number, that informsthe optimizing software the shipping cost of the items of bid 50. If abid taker 26 or exchange manager 24 desires to award a certainpercentage of the allocated bids to bidders living in a particularlocation, e.g., city, county, state, region, etc., the optimizingsoftware can be configured to determine the allocation of the bids basedon the data associated with the bid attribute bidder location rule 92-2.Similarly, the optimizing software can be configured to determine theallocation based upon the data associated with shipping cost rule 92-3.Other bid attributes that can be associated with a bid attribute rule 92include bidder reliability, bidder reputation, bidder timeliness,freight terms and conditions, insurance terms and conditions, bidderdistance and bidder flexibility.

[0083] Bid Adjustment Rule:

[0084] Bidder EDD 58 can also or alternatively have associated therewithone or more bid adjustment rules 100 that are similar syntactically tothe item adjustment rules previously described. Data associated with abid adjustment value rule 100-1 in FIG. 6b causes the optimizingsoftware to increase the price of bid 50 by $50 when “Excellent” 104-3associated with credit worthiness rule 92-1 is selected. If “Poor” 104-1or “Good” 104-2 associated with credit worthiness rule 92-1 is selected,however, the optimizing software will not change the price of bid 50.

[0085] Bid adjustment value rule 100-2 can have associated therewithexpressions and data that informs the optimizing software to increasethe price of a bid 50 by $25 when the data associated with shipping costrule 92-3 has a value between $50 and $100. Bid adjustment value rule100-2 can also have associated therewith a logical operator AND as aconnector between expressions. In addition to AND, the logical operatorsOR and NOT can also be utilized as connectors. Moreover, logicaloperators may be nested within other logical operators.

[0086] Bid adjustment value rule 100-2, causes the optimizing softwareto determine whether the actual shipping cost falls within the specifiedrange using tests. The first test determines if the actual shipping costis less than a first value, in this example $100. The second testdetermines if the actual shipping cost is greater than a second value,in this case $50. Each of these tests, i.e., “less than” and “greaterthan”, are from a group of operators over non-price attributes. Otheroperators include “equal to”, “less than”, “less than or equal to”,“greater than”, “greater than or equal to”, and “contains item”.

[0087] The expressions and data associated with each bid adjustmentvalue rule 100-1-100-3 are formatted as a conditional test. Namely, IFthe condition holds THEN the specified adjustment is applied. It isenvisioned that more complex expressions can be created that allow fordependence of whether the adjustment is applied based on multipleexpressions.

[0088] Bid adjustment value rule 100-3 has a “contains item” expressionassociated therewith that can be utilized for two purposes. First, ittests whether or not a bid contains an item, e.g., item 13. It should beappreciated that the “contains item” expression can only be used inconnection with a bid adjustment rule. In the example shown in FIG. 6b,bid adjustment value rule 100-3 informs the optimizing software toincrease the price of bid 50 by $10 when bid 50 contains item 13.Second, the “contains item” expression can be utilized for specifyingitem attributes inside of a bid adjustment. In the example shown in FIG.6b, bid adjustment value rule 100-3 informs the optimizing software toincrease the price of bid 50 by $10 when bid 50 contains item 13 and thecolor of item 13 is blue. If bid 50 does not include item 13, or if item13 is not blue, the optimizing software will not adjust the price of bid50 based on the expressions and data associated with bid adjustmentvalue rule 100-3.

[0089] Each bid adjustment value rule 100 is typically one of twoexemplary types: additive or multiplicative. An additive bid adjustmentvalue rule applies a positive (or negative) value to a bid if thecorresponding condition holds for the bid. An additive bid adjustmentvalue rule can either be absolute or per unit. An absolute additiveadjustment is applied to a bid if the corresponding condition holds. Aper unit additive bid adjustment rule is multiplied by the number ofunits of the item in the bid before application to the bid. Amultiplicative adjustment is only used with bid adjustments, not withitem adjustments. A multiplicative adjustment applies a specifiedpercentage correction to a value of a bid if the corresponding conditionholds. If the percentage is positive, the correction increases the valueof the bid. If the percentage is negative, the correction decreases thevalue of the bid. These particular adjustments are not to be construedas limiting the invention since the use of other suitable adjustments isenvisioned.

[0090] Bid taker EDD 60 can also or alternatively have associatedtherewith one or more bid adjustment rules 100 that inform theoptimizing software that the bid taker 26 is willing to adjust, forexample, a value the bid taker 26 pays or receives for one or more itemsif one or more conditions included in the bid taker EDD 60 are valid.

[0091] Constraint Rule:

[0092] With reference to FIGS. 7a-7 b, and with continuing reference toall previous figures, bidder EDD 58 and/or bid taker EDD 60 can also oralternatively have associated therewith one or more rules that imposeone or more limits on some aspect of the outcome of an allocation. Forexample, a rule can have data associated therewith for limiting themaximum number of winning buyers in a forward auction or the maximumnumber of winning sellers in a reverse auction. Another rule can havedata associated therewith for limiting the currency volume sold to anyone bidder. Still further, another rule can have data associatedtherewith for limiting the quantity of an item that a single suppliercan supply. The purpose of these rules is to enable the optimizingsoftware to determine one or more feasible allocations that meet theobjectives of the market. To this end, such rules are typicallyassociated with a bid or bid group by exchange manager 24. However, thisis not to be construed as limiting the invention. These rules cause theoptimizing software to determine the allocation in a manner thatconforms to desired minimum and/or maximum limits. Examples of suchrules include a cost constraint rule, a unit constraint rule, a countingconstraint rule, a homogeneity constraint rule and a mixture constraintrule, each of which will now be described.

[0093] Cost Constraint Rule:

[0094] As shown in FIG. 7a, bidder EDD 58 can also or alternatively haveassociated therewith a cost constraint rule 110 that causes theoptimizing software to restrict the winning allocation by establishing alimit that is based on winning bid prices and quantities. For example,cost constraint rule 110 can have associated therewith two bid groups112 and 114. Bid group 112 is a constrained group while bid group 114 isa control group. Bid group 114 is shown in FIG. 7a for illustrationpurposes, but it is assumed to be an empty group. There can be manyreasons to constrain a group of bids. For example, an exchange may havea need to limit the sum of the prices all of the bids from bidders in afirst city. Accordingly, a bid group is established with all of thebidders from the first city. It may also be desirable to limit thenumber of bidders from the first city as compared to a second city.

[0095] Cost constraint rule 110 of bidder EDD 58 causes the optimizingsoftware to compare the bid groups 112 and 114 with respect to the sumsof the prices of their winning bids. If the comparison is based onpercentage, then the sum of the prices of the winning bids associatedwith bid group 112 divided by that of the bid group 114 must be lessthan a value of a maximum limit 118 associated with cost constraint rule110 and greater than a value of a minimum limit 120 associated with costconstraint rule 110. For a comparison based on percentage, to avoiddivision by zero (0) when no bids are associated with bid group 114 orif bid group 114 does not exist, an imaginary second bid group (notshown) can be created that contains all of the winning bids. Thecomparison based on percentage is then determined by dividing the sum ofthe quantity of items of the bids allocated to bid group 112 by that ofthe imaginary second bid group and comparing the solution to the maximumlimit value and/or the minimum limit value.

[0096] If the comparison is absolute, then the sum of the prices of thebids associated with bid group 112 must be at least the minimum limitvalue more than that of the bids associated with bid group 114, and atmost the maximum limit value less than that of the bids associated withbid group 112.

[0097] For example, suppose that a forward auction includes a pluralityof bids where four bids 116-1-116-4 are made by bidders who fall into agroup of interest, e.g., bidders from Tucson, where it is desirable tolimit, based on cost, the value of the bids of this group. Suppose thatcost constraint rule 110 has associated therewith a percent maximumlimit 118 value of 25%. In this example, because it is desired to limitthe allocation as to the value of the bids of the Tucson bidders, bids116-1-116-4 are associated with bid group 112. This association causesthe optimizing software to limit the percentage of the total allocationawarded to the bidders of these bids to the percent maximum limit 118 ofcost constraint rule 110. In the example, if the sum of the values ofbids 116-1-116-4 exceed 25% of the total allocation value, the solutionis infeasible. If desired, cost constraint rule 110 can also oralternatively have associated therewith a minimum limit 120 which causesthe optimizing software to establish a lower limit on the totalallocation value.

[0098] Each cost constraint rule is strict a constraint in the sensethat it must be satisfied or the allocation is infeasible. For example,a cost constraint rule can limit a bidder to receive a minimum of atleast 50% of the total allocation value. Thus, if a bidder places a bidhaving a value of $11 in an exchange where the total allocation value ofthe exchange is $21, then the value of the cost constraint rule is$11/$21 or 52.38%. Since 52.38% is greater than the cost minimum limitof 50%, the allocation is feasible. However, if the cost constraintminimum is raised to 60%, the allocation is infeasible because 52.38% isless than 60%. In some situations, it may be desirable for the bidder tobe required to be awarded at least 50% of the allocation, or else beawarded no allocation.

[0099] Bid taker EDD 60 can also or alternatively have associatedtherewith a cost constraint rule, like cost constraint rule 110, thatinforms the optimizing software that the corresponding bid taker 26 isonly willing to buy or sell items subject one or more constraintsassociated with the cost constraint rule.

[0100] Cost Requirement Rule:

[0101] With reference to FIG. 7b, bidder EDD 58 can also oralternatively have associated therewith a cost requirement rule 130 thatcauses the optimizing software to withhold a bid or bid group from anallocation if a condition is not satisfied. Cost requirement rule 130 issyntactically similar to cost constraint rule 110. However, where costconstraint rule 110 can make a solution infeasible, cost requirementrule 130 enables the optimizing software to construct an allocationwhere a bid or bid group that otherwise would be allocated is withheldfrom the allocation because a constraint on the bid or bid group is notsatisfied. Stated differently, if a cost constraint rule is notsatisfied, the whole allocation is infeasible. In contrast, if a costrequirement rule is not satisfied, the bidder receives nothing, but theallocation is not necessarily infeasible.

[0102] For example, assume that a forward auction includes a pluralityof bids where four bids 132-1-132-4 are made by bidders who fall into agroup of interest, e.g., bidders from Tucson, where it is desired tolimit, based on cost, the value of the bids of the particular bidders.Suppose that cost requirement rule 130 has associated therewith apercent maximum limit 136 value of 25%. In this example, because it isdesired to limit the allocation as to the value of the bids of theTucson bidders, bids 132-1-132-4 are associated with bid group 134. Ifthe sum of the values of bids 132-1-132-4 exceeds 25% of the totalallocation value, the Tucson bidders receive nothing in the allocation.In order for the bids included in bid group 134 to be allocated, thepercent values of these bids must be less than the value of the percentassociated with maximum limit 136 of cost requirement rule 130. Ifdesired, cost requirement rule 130 can also or alternatively haveassociated therewith a minimum limit field 138 which causes theoptimizing software to set a lower limit on the percent of the totalallocation value.

[0103] Bid taker EDD 60 can also or alternatively include a costrequirement rule, like cost requirement rule 130, that informs theoptimizing software that the corresponding bid taker 26 is only willingto buy or sell one or more items if one or more constraints of bidderEDD 60 are satisfied. If the one or more constraints of bidder EDD arenot satisfied, the bid taker 26 receives nothing, but the allocation isnot necessarily infeasible.

[0104] Unit Constraint Rule:

[0105] With reference to FIG. 8a, bidder EDD 58 can also oralternatively have associated therewith a unit constraint rule 142 thatcauses the optimizing software to restrict the winning allocation bysetting a limit which is based on a quantity of items that are boughtand/or sold in winning bids. For example, unit constraint rule 142 canhave bid groups 144 and 146 and an item group 148 associated therewith.Suppose that a forward auction includes a plurality of bids where threebids 150-1-150-3 are made by one bidder where it is desired to limit thequantity of items awarded to that bidder. Moreover, suppose that thebidder is a buyer for a large computer discounter and that each of thethree bids is for as many units as are available of a new computer.Furthermore, suppose that 2000 of these computers are available and thatthere is a need to distribute some of the computers to other buyers inorder to facilitate the development of a wide customer base. Lastly,suppose that it is desired to limit the quantity of computers awarded tothe bidder of bids 150-1-150-3 to one-half of the available computers,or 1000 computers. Since it is desired to limit the bidder, bids150-1-150-3 are included in bid group 144 and the item associated withbids 150-1-150-3, i.e., a new computer, is included in item group 148. Asuitable value, in this example 1000, is associated with a maximum limit152 of unit constraint rule 142 to limit the maximum quantity ofcomputers the bids included in bid group 144 are awarded. In thisexample, bids 150-1-150-3 of bid group 144 can be awarded no more than1000 units. When the allocation is returned, the computer discounter isallocated no more than 1000 units by the optimizing software. Also oralternatively, a suitable value, in the example shown in FIG. 8a, 100,is associated with a minimum limit 154 of unit constraint rule 142 forlimiting the minimum quantity of units that are allocated to the bidsincluded in bid group 144. In this example, item group 148 includes onlycomputers. However, any part or item that would be useful to limit theallocation can also or alternatively be included in item group 148 or acorresponding item group.

[0106] As with cost constraint rules, there are two types of comparisonsthat can be made, namely, an absolute comparison, as in the foregoingexample of limiting the number of computers allocated to a computerdiscounter, and a comparison based on percentage. In a comparison basedon percentage, the sum of the quantity of items of the allocated bids inbid group 144 divided by the sum of the items of the allocated bids in abid group 146 must be less than a maximum percentage (not shown) and/orgreater than a minimum percentage (not shown). The maximum percentageand the minimum percentage can also be the same if the allocation of anexact percentage of items is desired. To avoid division by zero (0) whenbid group 146 does not exist or bid group 146 does not include any bids,a virtual second bid group (not shown) can be created that contains allof the winning bids. The comparison based on percentage is thendetermined by dividing the sum of the quantity of items of the winningbids of bid group 144 by that of the virtual second bid group andcomparing the solution to the value associated with the maximumpercentage and/or the minimum percentage.

[0107] For example, assume it is desired to limit the percentage ofitems awarded the bids included in bid group 144. Accordingly, a desiredpercentage (not shown) is associated with maximum limit 152 of unitconstraint rule 142. This percentage causes the optimizing software tolimit the percentage of available computers allocated to bids150-1-150-3 to the desired percentage.

[0108] Unit constraint rules, like cost constraint rules, are strict inthe sense that they must be satisfied or the allocation will beinfeasible. For example, a unit constraint rule can require a bidder toreceive at least 1000 units of an item in an auction. Thus, if a bidderplaces two bids that are allocated 500 units and 1000 units of the item,since this bidder satisfied the 1000 unit requirement, the allocation isfeasible. However, if the bidder places two or more bids, but the totalnumber of units of the item of all the bidder's bids does not add up to1000 units, then the solution is infeasible, and there is no allocationto the bidder.

[0109] Bid taker EDD 60 can also or alternatively include a unitconstraint rule, like unit constraint 142, that informs the optimizingsoftware that the corresponding bid taker 26 wishes to buy or sell nomore and/or no less than a certain number of units of one or more items.

[0110] Unit Requirement Rule:

[0111] With reference to FIG. 8b, bidder EDD 58 can also oralternatively have associated therewith a unit requirement rule 160 thatenables the optimizing software to allocate a quantity of zero to abidder to provide a winning allocation. Unit requirement rule 160 issyntactically similar to a unit constraint rule 142. However, where unitconstraint rule 142 makes the solution infeasible, unit requirement rule160 enables a quantity of zero to be allocated.

[0112] For example, suppose a forward auction includes a plurality ofbids where three bids 168-1-168-3 are made by a bidder to whom it isdesired to limit the quantity of awarded items. Suppose that the bidderis the buyer from the large computer discounter and the three bids arefor new computers. For this exchange, there is a need to sell all thecomputers as quickly as possible. Accordingly, it is desired to sell alarge quantity of the available computers to the computer discounter.Unit requirement rule 160 causes the optimizing software to allocate atleast 1000 computers to the bidder. Since it is desired to limit thebidder, unit requirement field 160 can have associated therewith a bidgroup 162 that includes bids 168-1-168-3 placed by the bidder. The itemsfor this example, i.e., new computers, are associated with an item group166. The number of units of the item associated with item group 166 thatare allocated to the bids included in bid group 162 is limited to thevalue, e.g., 1000, of minimum limit 170 of unit requirement rule 160 andby the value, e.g., 0, associated with a maximum limit 172 of unitrequirement rule 160. In this example, the bidder will be allocated 1000or more computers, or no computers. If the bidder is allocated nocomputers, however, the allocation is still feasible.

[0113] Bid taker EDD 60 can also or alternatively include a unitrequirement rule, like unit requirement rule 160, that informs theoptimizing software that the corresponding bid taker 26 is willing tobuy or sell a maximum and/or minimum quantity of units of one or moreitems.

[0114] Counting Constraint Rule:

[0115] With reference to FIG. 9a, bidder EDD 58 can also oralternatively have associated therewith a counting constraint rule 180that enables the optimizing software to control outcome parameters.Outcome parameters are those besides bid and item allocations and netexchange revenue. An example of an outcome parameter includes an imposedconstraint, such as an award of a minimum percentage of an allocation tominority firms. There may also be a market domination concern thatcompels an award of a maximum percentage of an allocation to one or agroup of bidders that may be specified. Another common example is toensure that a certain percentage of the business goes to a specificbidder, because of a long-standing business relationship. Still anotherexample is to condition an award to a bidder of at least a certainpercentage of the allocation to avoid giving the bidder such a smallamount of business that it does not cover the bidder's operatingexpenses.

[0116] For example, counting constraint rule 180 can have a value offour associated with a maximum limit 182 for controlling the maximumnumber of winning bidders. In FIG. 9a, each of six bidders has placed anumber of bids in the auction. The bids of each bidder are inserted intobid group 184-1-184-6, with bid group 184-1 including all the bidsplaced by bidder 1, with bid group 184-2 including all the bids placedby bidder 2, and so forth. The value of four associated with the maximumlimit 182 constrains the allocation made by the optimizing software tothe bids included in four of the six bid group 184-1-184-6. Since eachbid group 184 in this example represents one bidder, counting constraintrule 180 limits the number of winning bidders.

[0117] With continuing reference to FIG. 9a, suppose that value of zerois associated with the maximum limit 182 of counting constraint rule 180and a value of four is associated with a minimum limit 186 of countingconstraint rule 180. This will cause the winning allocation to includethe bids included in at most four of bid groups 184-1-184-6. Moreover,both the maximum limit 182 and the minimum limit 186 may include valueswherein the desired number of winning bidders falls within the range ofvalues.

[0118] Bid taker EDD 60 can also or alternatively include a countingconstraint rule, like counting constraint rule 180, that informs theoptimizing software that the corresponding bid taker 26 is willing tobuy or sell bids subject to one or more constraints included in thecounting constraint rule.

[0119] Counting Requirement Rule:

[0120] With reference to FIG. 9b, bidder EDD 58 can also oralternatively have associated therewith a counting requirement rule 190.The difference between a counting constraint rule and a countingrequirement rule is that the counting requirement rule can have aminimum limit value greater than zero, but also allow a value of zero.For example, suppose that counting constraint rule 180 in FIG. 9a has avalue of four associated with its minimum limit 186. Then, four or moreof bid groups 184-1-184-6 must be allocated or the solution isinfeasible. In contrast, suppose counting requirement rule 190 shown inFIG. 9b has a value of four associated with its minimum limit 192. Then,at least four of bid groups 194-1-194-6 must be allocated or none of bidgroups 194-1-194-6 will be included in the allocation. In either event,however, the allocation is still feasible.

[0121] Bid taker EDD 60 can also or alternatively include a countingrequirement rule, like counting requirement rule 190, that informs theoptimizing software that the corresponding bid taker 26 is willing tobuy or sell bids subject to one or more constraints included in thecounting requirement rule.

[0122] Homogeneity Constraint Rule:

[0123] With reference to FIG. 10, bidder EDD 58 can also oralternatively have associated therewith a homogeneity constraint rule200 that enables the optimizing software to place one or more limits onthe allocation. With a homogeneity constraint rule, a limit based on anitem attribute or a bid attribute can be placed on one or more bids. Forexample, in FIG. 5, item I1 52-1 has an item attribute color(s) rule78-1 associated therewith. Suppose, however, homogeneity constraint rule200 is needed to limit the number of represented colors in all of thespecified items of awarded bids, where the award of an item of greencolor is irrelevant, even though it is one of the colors for that itemattribute. Accordingly, homogeneity constraint rule 200 can be createdhaving a value of one associated with a color limit maximum 202 ofhomogeneity constraint rule 200. This value causes the optimizingsoftware to limit the colors included in the allocation to one color.

[0124] In response to receiving homogeneity constraint rule 200, theoptimizing software would cause the allocation to include items havingonly one of the colors of blue and red, but any number of green itemssince green was not included in an item attribute group of homogeneityconstraint rule 200. Thus, blue items or red items, and/or green itemsmay be allocated. As can be seen, homogeneity constraint rule 200ensures that no more than one of the specified colors will appear in theallocation. Since only the colors specified in homogeneity constraintrule 200 are considered for purposes of homogeneity, any other color, inthis example green, associated with color(s) item attribute rule 78 inFIG. 5 can also appear in the allocation. A color limit minimum (notshown) can also or alternatively be associated with homogeneityconstraint rule 200 for limiting the minimum number of colors of itemsawarded in the allocation or to establish a range of an item colorsawarded in an allocation.

[0125] The foregoing example shows one item per item attribute groups204, 206. However, multiple items may appear in each item attributegroups 204, 206. These items form an equivalence class for the purposeof homogeneity. For example, the color cyan can be considered to be thesame as the color blue when assessing homogeneity by adding cyan to itemattribute group 204.

[0126] Bid taker EDD 60 can also or alternatively include a homogeneityconstraint rule, like homogeneity constraint rule 200, that causes theoptimizing software to place one or more limits on the allocation.

[0127] Mixture Constraint Rule:

[0128] With reference to FIG. 11, bidder EDD 58 can also oralternatively have associated therewith a mixture constraint rule 210that enables the optimizing software to mix attributes of interest. Inthe previous example, homogeneity constraint rule 200 limited by maximumor minimum the different colors represented in all of the specifieditems of all of the bids of the allocation. Mixture constraint rule 210limits by attribute, similar to homogeneity constraint rule 200, butalso enables the optimizing software to select any combination of bidsor items in fulfilling that limit. For example, mixture constraint rule210 can have a value of twelve kg associated with an item weight maximum212 for an Item 1 associated with an item attribute weight 214 ofmixture constraint rule 210. The value associated with item weightmaximum 212 causes the optimizing software to limit the weight of allunits of Item 1 associated with item attribute weight 214 to an averageof no more than twelve kg. Mixture constraint rule 210 allowsheterogeneity in an allocation providing the average is within specifiedlimits. Therefore, in this example, suppose it is desired to have amixture of weights, providing the average weight is no more than twelvekg. With mixture constraint rule 210, it does not matter how the variousweights are mixed. The average value, which is constrained by theoptimizing software in response to mixture constraint rule 210, may bedetermined from any one or a combination of items. Mixture constraintrule 210 may also be price weighted, i.e., the prices of each bid willweight the average. For example, an attribute, e.g., item weight, on a$2 bid will have twice the effect the same attribute has on a $1 bid.

[0129] In the foregoing example, mixture constraint rule 210 isdescribed as enabling the optimizing software to operate on an itemattribute, i.e., weight. Mixture constraint rule 210, however, can alsoor alternatively be operative on a bid attribute of a bid group.Examples of exemplary bid attributes that mixture constraint rule 210can cause the optimizing software to operate on are described above inconnection with FIGS. 6a and 6 b.

[0130] Bid taker EDD 60 can also or alternatively have associatedtherewith a mixture constraint rule, like mixture constraint rule 210,that enables the optimizing software to mix attributes of interest tothe bid taker.

[0131] Cost Conditional Pricing Rule:

[0132] With reference to FIG. 12, bidder EDD 58 can also oralternatively have associated therewith a cost conditional pricing rule272 that causes the optimizing software to modify an outcome of aforward auction, a reverse auction or an exchange based on valuelimit(s). For example, two bid groups 274 and 276 can be associated withcost conditional pricing rule 272. Bid group 274 is a constrained bidgroup while bid group 276 is a control bid group. Bid group 276 iscreated for illustration purposes, but it is assumed that it is empty.Cost conditional pricing rule 272 is similar to cost constraint rule110, except that cost conditional pricing rule 272 causes the optimizingsoftware to utilize one or more cost constraints associated with amodifications group 278 of cost conditional pricing rule 272 to adjustthe solution rather than forcing the solution to obey other establishedconstraints. Advantages of changing a price outcome of an exchangeinclude, for example, the optimizing software giving a discount of $20to a buyer in a forward auction if the buyer spends more than $1000 or adiscount of $50 if the buyer spends more than $2000.

[0133] Bid taker EDD 60 can also or alternatively have associatedtherewith a cost conditional pricing rule, like cost conditional pricingrule 272, that includes one or more cost constraints that the optimizingsoftware utilizes to modify the allocation in a forward auction, areverse auction or an exchange based on value limit(s).

[0134] Unit Conditional Pricing Rule:

[0135] With reference to FIG. 13, bidder EDD 58 can also oralternatively have associated therewith a unit conditional pricing rule280 that causes the optimizing software to modify the value outcome of aforward auction, a reverse auction or an exchange based on a differencein unit volume of two or more bids or bid groups of two or more bidders.For example, two bid groups 282 and 284 can be associated with unitconditional pricing rule 280. Bid group 282 is a constrained group whilebid group 284 is a control group. In this example, bid group 284 is anempty group. Unit conditional pricing rule 280 causes the optimizingsoftware to operate in a manner similar to unit constraint rule 142 inFIG. 8a, except that unit conditional pricing rule 280 adjusts thesolution rather than forcing the solution to obey other constraint(s).For example, suppose bid group 282 includes all of the bids associatedwith buyer A and constraints or condition modifiers 286 and 288 areassociated with unit conditional price rule 280. The optimizing softwaredetermines a difference in unit volume between the item(s) associatedwith an item A associated with a modifications group 290, traded bybuyer A, associated with bid group 282, and the item(s) included in amodifications group 292 traded by the bidder(s), if any, associated withbid group 284. If the difference in unit volume awarded to the bidder(s)of bid group 282 and the unit volume awarded to the bidder(s) of bidgroup 284 is greater than the unit volume included in condition modifier286, a discount of $20 is given to the bidder(s) associated with the bidgroup 282 or 284 having the greater volume. If the difference is greaterthan the unit volume included in condition modifier 288, a discount of$50 is given to bidder(s) associated with the bid group 282 or 284having the greater volume.

[0136] In the example shown in FIG. 13, since modifications group 292and bid group 284 are empty, the unit volume is the number of units ofitem A listed in modifications group 290 traded by the bidder associatedwith bid group 282. Unit conditional pricing rule 280 uses thedifference in the unit volumes included in bid groups 282 and 284. Inthis example, since bid group 284 includes no bids, its unit volumedefaults to empty and the difference is simply the unit volume of thebids of bid group 282 for buyer A. If the unit volume of the bids of bidgroup 282 is 1000 units or more than the unit volume of the bids of bidgroup 284, the optimizing software determines that condition modifier286 is satisfied and a discount of $20.00 is given. If the unit volumeincluded in bid group 282 is 2000 units or more than the unit volumeincluded in bid group 284, the optimizing software determines thatcondition modifier 288 is satisfied and a discount of $50.00 is given.

[0137] Bid taker EDD 60 can also or alternatively have associatedtherewith a unit conditional pricing rule, like unit conditional pricingrule 280, that includes one or more conditions that the optimizingsoftware utilizes to modify the value outcome of a forward, a reverseauction or an exchange based on a difference in unit volume of two orbids or bid groups of two or more bidders.

[0138] Quote Request Rule:

[0139] Bidder EDD 58 can also or alternatively have associated therewitha quote request rule (not shown) that causes the optimizing software totreat the corresponding bid 50 as a “quote request”, whereupon theoptimizing software returns to the bidder of the bid a price where thebid would just be included in an allocation, i.e., the least competitiveprice. Thereafter, if the bidder wishes to place one or more bids orassociate one or more bids with a bid group that the optimizing softwareconsiders for inclusion in an allocation, such bid can be made or suchbid group can be formed separately from the quote request rule. Thus,the optimizing software treats a quote request rule like a bid.

[0140] Bid taker EDD 60 can also or alternatively have associatedtherewith a quote request rule that causes the optimizing software toreturn to the corresponding bid taker 26 a price of a bid that wouldjust be included in an allocation.

[0141] As can be seen, bidder EDD 58 and/or bid taker EDD 60 can includeone or more of the foregoing rules that the optimizing software canutilize to determine an allocation. Next, the rules that are typicallyassociated uniquely with bid taker EDD 60 will be described. These rulesinclude an objective rule, a constraint relaxer rule and a feasibilityobtainer rule.

[0142] Objective Rule:

[0143] With reference to FIG. 14, bid taker EDD 60 can have associatedtherewith an objective rule 257 that establishes a maximization orminimization goal that the optimizing software utilizes to determine anallocation value for an exchange. Each maximization goal has onespecific meaning for forward auctions, reverse auctions, and exchanges.Each minimization goal has one specific meaning for a reverse auction.

[0144] Objective rule 257 can comprise one or more rules related to oneor more objectives of an exchange. These exchange objectives includesurplus, traded bid volume, traded ask volume or traded average volume.Each of these rules expresses a maximization goal for a forward auctionor exchange, or a minimization goal for a reverse auction. The followingtable shows the rule(s) associated with objective rule 257 for theforegoing objectives of the exchange. Objective Forward Auction ReverseAuction Exchange Surplus sum of accepted N/A sum of accepted bids lessthe sum of bids less sum of their item reserve accepted asks pricesTraded bid sum of accepted N/A sum of accepted bids bids Traded ask sumof item sum of accepted sum of accepted reserve prices of asks asksaccepted bids Traded average of the sum N/A average of the average ofaccepted bids and sum of accepted sum of their item bids and sum ofreserve prices accepted asks

[0145] The rules associated with each of the foregoing objectivesenables the optimizing software to perform a specific optimization. Eachobjective is useful because it enables specification of exactly what iswanted in a forward auction, reverse auction or exchange. For example,suppose one unit of three items, namely, item A 260, item B 262 and itemC 264, for sale at prices of $100, $45 and $45, respectively, areincluded in an ask group 258 associated with objective rule 257 of bidtaker EDD 60. These are ask bids since the three items are being sold.Moreover, suppose that a buy group 265 associated with objective rule257 includes three buy bids: Bid 1 266 for Item A for $100; Bid 2 268for Items B and C for $105; and Bid 3 270 for Item C for $70.Furthermore, suppose that these three buy bids are logically connectedby XOR (exclusive OR) logical operators whereupon only one of Bids 266,268 and 270 will be allocated by the optimizing software.

[0146] If an exchange objective 271 of objective rule 257 is set to“maximize traded ask”, Bid 1 266 is allocated by the optimizing softwaresince it has the maximum ask value, i.e., $100. If exchange objective271 is set to “maximize traded bid”, Bid 2 268 is allocated by theoptimizing software since it has the maximum bid value, i.e., $105. Ifexchange objective 271 is set to “maximize surplus”, Bid 3 270 isallocated by the optimizing software since it has the largest surplusvalue, i.e., $70-$45=$25. Lastly, if exchange objective 271 is set to“maximize traded average”, either Bid 1 for Item A 260 at $100, or Bid 2for Items B and C 262 and 264 at $105 is allocated by the optimizingsoftware. Exchange objective 271 can also be set to “maximize the numberof winning bidders” or “maximize the number of losing bidders” in anallocation. In each of the foregoing settings, the word “maximize” canbe replaced with “minimize” whereupon the optimizing software will beprovided with the corresponding rule.

[0147] Constraint Relaxer Rule:

[0148] With reference to FIGS. 15 and 16, many of the rules describedthus far have the capacity to be relaxed by a bid taker 26. Accordingly,bid taker EDD 60 can also or alternatively have associated therewith aconstraint relaxer rule 220. The ability to relax a rule has twopurposes, namely, to obtain candidate allocations when the originalproblem does not have a feasible allocation, and to search foralternative allocations when there is a feasible allocation. Suchalternative allocations can illustrate the impact on the allocationsolution as more important rules are relaxed. The importance of eachrule can depend on the relative relaxation importance weight assignedthereto. These weights are dependent on the weights and types of eachrule in an exchange.

[0149]FIG. 15 illustrates a constraint relaxer rule 220 that includesone or more possible desired solutions 222, 224 and 226 that can beapplied by the optimizing software to determine an exchange allocation.For example, selecting constrained solution 222 causes the optimizingsoftware to search for an allocation with all the constraints in place.Selecting unconstrained solution 226 causes the optimizing software tosearch for an allocation with no constraints in place. Betweenconstrained and unconstrained solutions 222 and 226, there is relaxationsolution 224. Selecting relaxation solution 224 causes the optimizingsoftware to search for one or more allocations as a function of “soft”and/or “hard” properties. For example, in FIGS. 7a and 9 a, “soft”properties 228 and 236 are associated with cost constraint rule 110 andcounting constraint rule 180, respectively, while in FIG. 8a, a “hard”property 232 is associated with unit constraint rule 142. Whenrelaxation solution 224 is selected in constraint relaxation rule 220,the optimizing software obtains a feasible solution by relaxing costconstraint rule 110 and counting constraint rule 180 while maintainingunit constraint rule 142. In this example, the use of “hard” property232 in FIG. 8a assumes that unit constraint rule 142 is so importantthat to relax it will create a useless allocation.

[0150] Selecting constrained solution 222 causes the optimizing softwareto create the exemplary constrained allocation 240 shown in FIG. 16.Namely, a fully constrained allocation for which either a feasible,market desirable solution or an infeasible solution exists. In otherwords, constrained allocation 240 shows the bids that should be awardedgiven all of the bids and all of the rules associated with bidder EDDs58 and/or bid taker EDDs 60. In the example shown in FIG. 16,constrained allocation 240 shows three winning bids with an allocationvalue of $1,000.

[0151] In contrast, selecting relaxation solution 224 causes theoptimizing software to relax each rule that has a “soft” propertyassociated therewith to obtain the exemplary relaxation allocation 242shown in FIG. 16. Selecting unconstrained solution 226 causes theoptimizing software to relax all of the rules associated with bidderEDDs 58 and/or bid taker EDDs 60 to obtain the exemplary unconstrainedallocation 244 shown in FIG. 16. Relaxed allocation 242 andunconstrained allocation 244 illustrate other useful allocations that donot necessarily meet all of the constraints. For example, relaxedallocation 242 shows a total of five winning bids with an allocationvalue of $4,000 while unconstrained allocation 242 shows a total of sixbids with an allocation value of $5,000. Unconstrained allocation 244illustrates the effect of imposing no rules on the allocation of bids bythe optimizing software.

[0152] With reference back to FIGS. 7a, 7 b, 9 a and 9 b, relaxationimportances 250, 252, 254 and 256 can be associated with rules 110, 130,180 and 190, respectively. The use of these relaxation importances willnow be described.

[0153] In FIG. 7a, cost constraint rule 110 has a value of ten includedin relaxation importance 250. In FIG. 9a, counting constraint rule 180includes a value of twenty in relaxation importance 254. Cost constraintrule 110 has a “soft” property 228 associated therewith and countingconstraint rule 180 has a “soft” property 236 associated therewith. Ifthe optimizing software determines that cost constraint rule 110 orcounting constraint rule 180 can be relaxed to obtain a feasibleallocation, but it is not necessary to relax both, then cost constraintrule 110 having a value of ten in its relaxation importance 250 would berelaxed instead of relaxing counting constraint rule 180 having a valueof twenty in its relaxation importance 254.

[0154] In response to selecting relaxation solution 224 in FIG. 15, theoptimizing software finds a feasible allocation while relaxingconstraints according to the value included in the correspondingrelaxation importance, if any. The greater the value included in therelaxation importance, the less likely the associated rule(s) will berelaxed. Relaxation solution 222 can also have an associated cost, e.g.,1000, which specifies the weight of the relaxation to be applied by theoptimizing software. The relaxation cost is calculated by aggregating,over all relaxed rules, the amount by which the rule(s) are violatedmultiplied by the value included in the corresponding relaxationimportance. The value associated with a relaxation importance causes theoptimizing software to maximize or minimize one or more rules minus therelaxation cost associated with relaxation solution 224. For example, ifrelaxation solution 242 has a cost of 1000 associated therewith andanother relaxation solution (not shown) has a cost of 2,000 associatedtherewith, and if both relaxation solutions are selected, the optimizingsoftware will relax the rule(s) associated with the latter relaxationsolution before relaxing the rules of the former relaxation solution.Thus, in this example, the optimizing software would determine anoptimal allocation based on the relaxation solution having the greatercost.

[0155] Feasibility Obtainer Rule:

[0156] Bid taker EDD 60 can also or alternatively have associatedtherewith a feasibility obtainer rule (not shown) which causes theoptimizing software to minimize the relaxation cost, instead ofminimizing or maximizing objective rule(s), discussed above inconnection with FIG. 14, minus a relaxation cost. More specifically, afeasibility obtainer rule causes the optimizing software to generatefeasible allocations when a winning allocation with all of the rulesactive is unavailable. For example, suppose that constrained solution222 of constraint relaxation rule 220 is selected. In response to thisselection, the optimizing software will only attempt to generate awinning allocation. However, if bid taker EDD 60 includes a feasibilityobtainer rule and the optimizing software determines that a feasible,constrained allocation cannot be found, it relaxes one or more rules inan attempt to find a feasible allocation.

[0157] As can be seen, bidder EDDs 58 and bid taker EDDs 60 enablebidders 22, bid takers 26 and/or exchange manager 24 to modify how theoptimizing software determines an optimal allocation. This may beperformed iteratively in order to see the effects of these modificationson the winning allocations.

[0158] The optimizing software can include suitable controls forterminating the determination of an allocation. One control is a maximumprocessing time whereupon, when the maximum processing time is reached,the optimizing software terminates processing of the bids and reportsthe best allocation found. Another control compares the best allocationfound at any point in time with an optimal allocation, i.e., anallocation with all rules relaxed. If the difference between these twoallocations reaches a predetermined value, the optimizing softwareterminates processing and reports the best allocation found. Anothercontrol is a manual abort that can be issued by, for example, theexchange manager. In response to receiving this manual abort, theoptimizing software terminates processing and reports the bestallocation found.

[0159] Live, Expressive Combinatorial Exchanges:

[0160] In a live, expressive combinatorial exchange, e.g., a pureexchange, a forward auction or a reverse auction, it is desirable toprovide feedback regarding the exchange to bidders, especially eachbidder having a bid not included in an allocation, and/or bid takers inorder to enhance competition and, potentially, make subsequent biddingand/or bid taking easier. A method of conducting a live, expressivecombinatorial exchange will now be described with reference to FIG. 17,and with reference back to FIG. 3.

[0161] The method commences at start step 300 with exchange manager 24initiating the exchange event. The method then advances to step 302where the exchange manager 24 receives from each of a plurality ofbidders 22 at least one bid 50 comprised of at least one item 52, aninitial quantity 54 of each item 52, and a price 56 for all of theitem(s) and their quantities 54.

[0162] At a suitable time, the method advances to step 304 where theoptimizing software determines from the received bids an allocation thatis optimal for the type of exchange being conducted. In a livecombinatorial exchange, each bid 50 that is part of the allocation willinclude all of the items 52 of the bid 50 and at least part of theinitial quantity 54 of each item 52. For example, if an allocationincludes a bid 50 that includes item I1 52-1 and item I2 52-2, all orpart of the quantity Q1 54-1 of item I1 52-1 will be included in theallocation and all or part of the quantity Q2 54-2 of item I1 52-1 willbe included in the allocation.

[0163] Once the allocation has been determined, the method advances tostep 306 where at least a portion of each bid of the allocation isreturned to each bidder of a first subset of the bidders 22 that has atleast one bid that is not included in the allocation for display on thedisplay 18 of the computer system 2 of said bidder.

[0164] The method then advances to step 308 where each bidder of asubset of the first subset of bidders submits to exchange manager 24 anew bid and/or an amendment to an existing bid for processing by theoptimizing software.

[0165] The method then advances to step 310 where a determination ismade whether a predetermined condition is satisfied. If so, the methodadvances to stop step 312 and the exchange event terminates. However, ifthe predetermined condition is not fulfilled, the method returns to step304 where, at a suitable time, the optimizing software determinesanother allocation that is optimal for the type of exchange beingconducted. The bids processed by the optimizing software in this latteriteration of step 304 include all the bids from the immediatelypreceding iteration of step 304, including any amendments thereto in theimmediately preceding iteration of step 308, along with any new bidsreceived in the prior iteration of step 308. Once the other allocationhas been determined in step 304, steps 306-310 are repeated. Thereafter,providing the predetermined condition in step 310 is not satisfied,steps 304-308 are repeated at suitable times during the course of theexchange event, e.g., periodically, after a predetermined number ofbid(s) have been received, after each new or amended bid is received,etc., until the predetermined condition is satisfied whereupon themethod advances to stop step 312 and the exchange event terminates.

[0166] As can be seen from the flowchart of FIG. 17, in step 306, eachbidder not having a bid included in an allocation is provided with dataregarding the bids that were included in the allocation. Based on thisdata, the bidder can do nothing, or, as shown in step 308, the biddercan amend an existing bid to make it more competitive whereupon it maybe included in the allocation the next time step 304 is executed, orplace a new bid that may be included in the next allocation the nexttime step 304 is executed. The process of determining an allocationbased on received bids, providing feedback regarding the bids includedin the allocation to bidders whose bids are not included in theallocation, receiving new or amended bids from at least some of thebidders provided with said feedback, and determining another allocationbased on the new or amended bids and any other previously received bidscontinues until the predetermined condition is satisfied.

[0167] The predetermined condition can include, among other things, (i)a lapse of a predetermined time interval from commencement of theexchange, (ii) a manual abort, or (iii) a sum of prices of the bids ofthe allocation reaching a predetermined value.

[0168] The purpose of causing at least a portion of each bid included inthe allocation to be displayed to each bidder that has at least one bidthat is not included in the allocation is to enable the bidder to moreeffectively compete by facilitating the bidder's formulation of a newbid or an amendment to an existing bid that may result in the new bid oramended bid being included in the next allocation the next time step 304is executed.

[0169] Supplying information regarding only one of the bids included inthe allocation to bidders having at least one bid not included in theallocation is of little or no value in a combinatorial exchange sincedoing so does not provide sufficient information from which the biddersof bids not included in the allocation can formulate new bids oramendments to existing bids that will improve their chance of having abid included in the next allocation.

[0170] Each bid of a subset of the bids can have bidder EDD 58associated therewith. As discussed above, bidder EDD 58 comprises one ormore rules for processing the associated bid, at least one item of theassociated bid, and/or a subset of bids that includes all or less thanall of the bids when determining the allocation.

[0171] When determining the allocation in step 304, the optimizingsoftware desirably determines the allocation based on the bids receivedup to that time, i.e., new bids, amended bids and/or any other receivedbids, along with any bidder EDD associated with said bids. Thus, if eachbid of a subset of the bids has bidder EDD associated therewith, theoptimizing software determines the allocation based on all of thereceived bidder EDDs along with all of the received bids. The portion ofeach bid of the allocation that is displayed to each bidder of a firstsubset of bidders that has at least one bid that is not included in theallocation can include at least one item of the bid included in theallocation, the quantity of the at least one item of the bid, the pricefor all the item(s) and their quantities and/or at least a portion ofthe received bidder EDD 58 associated with the bid. The exchange manager24 desirably sets the at least portion of each bid of the allocationthat is displayed. However, this is not to be construed as limiting theinvention.

[0172] Amending an existing bid in step 308 can include adding at leastone new rule to bidder EDD 58 associated with the bid, deleting at leastone rule from the bidder EDD 58 associated with the bid, amending avalue associated with at least one rule of the bidder EDD 58 associatedwith the bid, amending a value of the quantity of at least one item ofthe bid, and/or amending the price for all of the items and theirquantities.

[0173] Also or alternatively, the allocation can be determined in step304 based on bid taker EDD 60. As discussed above, each bid taker EDD 60comprises at least one rule (or constraint) for processing at least oneof a bid, at least one item of a bid, and a subset of the plurality ofthe bids.

[0174] If desired, step 306 can include providing all or part of eachbid taker EDD 60 to each bidder and/or bid taker participating in theexchange. Providing all or part of each bid taker EDD to each bidderparticipating in the exchange facilitates the bidder's formulation ofone or more new or amended bids of the bidder to improve the bidder'schance of having one or more bids included in the next allocation thenext time step 304 is executed. Providing each bid taker participatingin the exchange with all or a portion of each bid taker EDD 60facilitates the bid taker's formulation of one or more new or amendedbid taker EDDs 60 to maintain or improve the bid taker's competitivenessin subsequent iterations of step 304. Amendments to an existing bidtaker EDD can include adding at least one new rule to the existing bidtaker EDD, deleting at least one rule from the existing bid taker EDD,and/or amending a value associated with at least one rule of theexisting bid taker EDD.

[0175] If desired, step 308 can include receiving from each bid taker ofa subset of the bid takers at least one of a new bid taker EDD and anamendment to an existing bid taker EDD of the bid taker. The amendmentto the existing bid taker EDD of the bid taker can include adding atleast one new rule to the existing bid taker EDD, deleting at least onerule from the existing bid taker EDD, and amending a value associatedwith at least one value of the existing bid taker EDD.

[0176] Bidder EDDs 58 and bid taker EDDs 60 can be utilized by theoptimizing software either alone or in combination to determine theallocation.

[0177] A portion of at least one bid included in the allocation can alsobe provided to each bidder of a second subset of bidders that has atleast one bid that is part of the allocation, i.e., winning bidders, fordisplay on the display 18 of the computer system 2 of said bidder. Thepurpose of displaying the at least portion of each bid included in thewinning allocation to bidders having bids included in the winningallocation is to facilitate the formulation by each said bidder of a newbid or an amended bid that may result in said new bid or amendment bidbeing included in the allocation the next time step 304 is executed.

[0178] The portion of the at least one bid included in the allocationthat is displayed on the display 18 of the computer system 2 of awinning bidder can include at least one item of the bid, the initial orallocated quantity of the at least one item of the bid, the price forall of the item(s) and/or quantities, and/or at least a portion of thebidder EDD associated with the bid.

[0179] In the foregoing description, each subset of bidders includes allor less than all of the plurality of bidders. Moreover, each subset ofbids includes all or less than all of the received bids.

[0180] Rule Selection:

[0181] Each rule of each bidder EDD 58 established by a bidder 22 isdesirably selected from a predetermined set of bidder rules establishedand maintained by the exchange manager 24 for the exchange event.Similarly, each rule of each bid taker EDD 60 established by a bid taker26 is desirably selected from a predetermined set of bid taker rulesestablished and maintained by the exchange manager 24 for the exchangeevent. Limiting the rules each bidder and bid taker can utilize in anexchange event enables the exchange manager 24 to better control theconduct of the exchange event.

[0182] Supervisory Constraint:

[0183] To further enable exchange manager 24 to control the conduct ofthe exchange event, each rule of a subset of the rules, i.e., all orless than all of rules, can also or alternatively have an exchangemanager controllable supervisory constraint imposed thereon. Under thecontrol of exchange manager 24, each supervisory constraint can imposeone or more limits on at least one of (1) the addition of thecorresponding rule to an EDD, (2) the deletion of the corresponding rulefrom an EDD, (3) the relaxation of the corresponding rule of an EDD,and/or (4) the tightening of the corresponding rule of an EDD.

[0184] Examples of the use of a supervisory constraint include: allowingor forbidding bidders and/or bid takers from adding or deleting thecorresponding rule to or from an EDD; forcibly adding or deleting thecorresponding rule to or from an EDD; allowing or forbidding biddersand/or bid takers to relax or tighten the corresponding rule, e.g.,relaxing or tightening the maximum (or minimum) number of winnerspermitted in an allocation; and forcibly relaxing or tightening thecorresponding rule. The listing of the foregoing examples is not beconstrued as limiting the invention since other uses of a supervisoryconstraint are envisioned.

[0185] Desirably, exchange manager 24 can selected when each supervisoryconstraint is active or inactive during an exchange event. If asupervisory constraint is inactive there are no limits on the use of thecorresponding rule. However, if a supervisory constraint is active, theone or more limits associated with the supervisory constraint areimposed on the corresponding rule. For example, a supervisory constraintcan be activated on or before an exchange event commences and can remainactive throughout the exchange event whereupon the limit(s) associatedwith the supervisory constraint are imposed on the corresponding rule.In another example, a supervisory constraint can be inactive when theexchange event commences, but can be activated during the course of anexchange event and remain active throughout the remainder of theexchange whereupon the bidders and/or bid takers use of the rules and,hence, the conduct of the exchange event is altered. In yet anotherexample, a supervisory constraint can be active when the exchange eventcommences, but can be inactivated during the course of an exchange eventand remain inactive throughout the remainder of the exchange event toalter the conduct of the exchange event. The foregoing examples of whena supervisory constraint is or becomes active or inactive are not to beconstrued as limiting the invention.

[0186] Exchange Prolongation:

[0187] As discussed above, one predetermined condition for terminating alive, combinatorial exchange is the lapse of a predetermined timeinterval from commencement of the exchange event. Under certainconditions, however, it may be desirable to extend the predeterminedtime interval. One such condition includes the receipt of a bid within apredetermined duration of the end of the predetermined time intervalthat improves the allocation. For example, if a new or amended bid thatimproves the allocation is received within, for example, one minute ofthe end of the exchange, the predetermined time interval can be extendedfor a predetermined extension interval, e.g., five minutes. This processof extending the predetermined time interval can be repeated as desired.

[0188] In an exchange that includes plural bidders and plural bidtakers, the allocation improves if (i) the number of items exchangedincreases or (ii) if a difference between a sum of the prices of the buybids and a sum of the prices of the sell bids of the allocationincreases. In an exchange that includes plural buyers and a singleseller ( forward auction), the allocation improves if a sum of theprices of the bids of the allocation decreases. Lastly, in an exchangethat includes a single buyer and plural sellers ( reverse auction), theallocation improves if a sum of the prices of the bids of the allocationincreases.

[0189] Logical Bid Combinations:

[0190] To facilitate processing of the bids by the optimizing software,all of the bids 50 received from bidders 22 can be logically OR'edtogether and two or more bids 50 received from the same bidder that haveat least one item in common can be logically XOR'ed together. Thiscombination of logical operators enables each bidder to place two ormore bids for the same item without concern that the optimizing softwarewill include said two or more of bids in the allocation whereupon thebidder is awarded more than a desired quantity of the item.

[0191] Bidder Identification:

[0192] In step 306 of the flowchart shown in FIG. 17, when at least aportion of each bid of the allocation is caused to be displayed to afirst subset of bidders that has at least one bid that is not includedin the allocation, an identification of the bidder of the bid can alsobe caused to be displayed. If desired, the displayed bidderidentification can be obscured in the sense that the identity of theactual bidder is not clear from the displayed bidder identification.

[0193] Precondition and Decisional Construct:

[0194] At least one rule can be introduced into at least one bidder EDDin response to a bidder specifying (i) a precondition of said rule and(ii) an effect to apply if said precondition is satisfied. Theprecondition can include a scope, e.g., a specific geographical region,a specific group of items or item category, or a time window, such assecond quarter, that the rule applies to, and a comparison for thescope, e.g., a total dollar volume greater than a predetermined dollarvolume. Examples of effects that can be applied include giving a threepercent discount on some subset of bids, determine the allocation to beinfeasible, give a three percent handicap to the bids of a specificsubset of bidders. For example, if the total dollar volume exceeds thepredetermined dollar volume in a specific geographical region (theprecondition), the rule is associated with the appropriate bidder EDDwhereupon the effect of the rule is considered when determining theallocation. In contrast, if the total dollar volume does not exceed thepredetermined dollar volume, the rule is not associated with the bidderEDD. Similarly, at least one rule associated with at least one bid takerEDD can be associated therewith in response to a bid taker specifying(i) a precondition of said rule and (ii) an effect to apply if saidprecondition is satisfied. The bidder and/or the bid taker desirablyutilizes a graphical user interface on a display 18 of a computer 2 tospecify the precondition and the effect.

[0195] The invention has been described with reference to the preferredembodiments. Obvious modifications and alterations will occur to othersupon reading and understanding the preceding detailed description. Forexample, the foregoing examples are for the purpose of illustration andare not to be construed in any way as limiting the invention. It isintended that the invention be construed as including all suchmodifications and alterations insofar as they come within the scope ofthe appended claims or the equivalents thereof.

The invention claimed is:
 1. A method of conducting a live combinatorialexchange comprising: (a) receiving from each of a plurality of biddersat least one bid comprised of at least one item, an initial quantity ofeach item, and a price for all of the item(s) and their quantities; (b)determining an allocation that is optimal for the type of exchange beingconducted, wherein said allocation includes a plurality of bids witheach bid of said allocation including all of the items of the bid and atleast part of the initial quantity of each item; (c) causing at least aportion of each bid of said allocation to be displayed to each bidder ofa first subset of the bidders that has at least one bid that is notincluded in said allocation; (d) receiving from each bidder of a subsetof the first subset of bidders at least one of a new bid and anamendment to an existing bid of the bidder; and (e) repeating steps(b)-(d) until a predetermined condition is satisfied.
 2. The method ofclaim 1, wherein each item includes one of a tangible good, a serviceand money.
 3. The method of claim 1, wherein the predetermined conditionincludes at least one of (i) a lapse of a predetermined time intervalfrom commencement of the exchange, (ii) a manual abort, and (iii) a sumof the prices of the bids of the allocation reaching a predeterminedvalue.
 4. The method of claim 1, wherein: each bid of a subset of thebids has associated therewith exchange description data (EDD)established by the bidder of said bid (bidder EDD); bidder EDD comprisesat least one rule (or constraint) for processing at least one of (i) abid, (ii) at least one item of a bid, and (iii) a subset of bids thatincludes all or less than all of the bids when determining theallocation; and step (b) further includes determining the allocation asa function of bidder EDD.
 5. The method of claim 4, wherein bidder EDDincludes at least one rule related to: bid attribute(s), bidadjustment(s), item attribute(s), item adjustment(s), free disposal,action, cost constraint/requirement, unit constraint/requirement,counting constraint/requirement, homogeneity constraint, mixtureconstraint, cost/unit condition pricing, quote request and reserveprice(s).
 6. The method of claim 4, wherein the portion of each bid instep (c) includes at least one of: (i) the at least one item of the bid,(ii) the quantity of the at least one item of the bid, (iii) the pricefor all of item(s) and their quantities, and (iv) at least a portion ofthe bidder EDD.
 7. The method of claim 1, further including displaying aportion of at least one bid that was determined to be part of theallocation to each bidder of a second subset of bidders that has atleast one bid that is part of the allocation.
 8. The method of claim 7,wherein: each subset of bidders includes (i) all or (ii) less than allof the plurality of bidders; and each subset of bids includes (i) all or(ii) less than all of the bids.
 9. The method of claim 7, wherein theportion of the at least one bid in step (c) includes at least one of:(i) at least one item of the bid, (ii) the initial or allocated quantityof at least one item of the bid, (iii) the price for all of item(s) andtheir quantities, and (iv) at least a portion of the bidder EDD.
 10. Themethod of claim 1, wherein the exchange is one of a forward auction anda reverse auction.
 11. The method of claim 4, wherein the amendment tothe existing bid in step (d) includes at least one of: the addition ofat least one new rule to bidder EDD associated with the existing bid;the deletion of at least one rule from bidder EDD associated with theexisting bid; the amendment of a value associated with at least one ruleof bidder EDD associated with the existing bid; the amendment of a valueof the quantity of at least one item of the existing bid; and theamendment of the price for all of item(s) and their quantities.
 12. Themethod of claim 11, further including imposing at least one supervisoryconstraint that limits at least one of (i) adding at least one rule to abidder EDD, (ii) deleting at least one rule from a bidder EDD, (iii)relaxing at least one rule of a bidder EDD and (iv) tightening of atleast one said rule of a bidder EDD.
 13. The method of claim 4, wherein:step (b) further includes determining the allocation based on EDDestablished by a bid taker (bid taker EDD); and step (d) furtherincludes receiving from the bid taker at least one of a new bid takerEDD and an amendment to an existing bid taker EDD of the bid taker,wherein the amendment to the existing bid taker EDD of the bid takerincludes at least one of: adding at least one new rule to the existingbid taker EDD; deleting at least one rule from the existing bid takerEDD; and amending a value associated with at least one rule of theexisting bid taker EDD.
 14. The method of claim 3, further includingextending the predetermined time interval in response to receiving a bidthat improves the allocation within a predetermined duration of the endof the predetermined time interval.
 15. The method of claim 14, wherein:in an exchange that includes plural bidders and plural bid takers, theallocation improves when (i) the number of items exchanged increases or(ii) a difference between a sum of the prices of the buy bids and a sumof the prices of the sell bids of the allocation increases; in anexchange that includes a single buyer and plural sellers (reverseauction), the allocation improves if a sum of the prices of the bids ofthe allocation decreases; and in an exchange that includes a singleseller and plural buyers (forward auction), the allocation improves if asum of the prices of the bids of the allocation increases.
 16. Themethod of claim 1, further including: OR'ing all the received bids; andXOR'ing bids received from one bidder that include at least one item incommon.
 17. The method of claim 1, wherein: step (b) further includesdetermining the allocation as a function of exchange description data(EDD) established by a bid taker (bid taker EDD), wherein bid taker EDDcomprises at least one rule (or constraint) for processing at least oneof (i) a bid, (ii) at least one item of a bid, and (iii) a subset of theplurality of the bids when determining the allocation; and step (d)further includes receiving from the bid taker at least one of new bidtaker EDD and an amendment to an existing bid taker EDD of the bidtaker, wherein the amendment to the existing bid taker EDD of the bidtaker includes at least one of: adding at least one new rule to theexisting bid taker EDD; deleting at least one rule from the existing bidtaker EDD; and amending a value associated with at least one rule of theexisting bid taker EDD.
 18. The method of claim 17, further includingimposing at least one supervisory constraint that limits at least one of(i) adding at least one rule to a bid taker EDD, (ii) deleting at leastone rule from a bid taker EDD, (iii) relaxing at least one rule of a bidtaker EDD and (iv) tightening of at least one said rule of a bid takerEDD.
 19. The method of claim 17, wherein bid taker EDD includes at leastone rule related to: objective(s), constraint relaxer(s), feasibilityobtainer(s), bid adjustment(s), item attribute(s), item adjustment(s),free disposal, action, cost constraint/requirement, unitconstraint/requirement, counting constraint/requirement, homogeneityconstraint, mixture constraint, cost/unit condition pricing, quoterequest and reserve price(s).
 20. The method of claim 1, wherein step(c) further includes causing an identification of the bidder of the bidto be displayed.
 21. The method of claim 20, wherein the display of thebidder identification is obscured.
 22. The method of claim 4, wherein atleast one rule is introduced into at least one bidder EDD in response toa bidder specifying (i) a precondition of said rule and (ii) an effectto apply if said precondition is satisfied.
 23. The method of claim 17,wherein at least one rule is introduced into at least one bid taker EDDin response to a bid taker specifying (i) a precondition of said ruleand (ii) an effect to apply if said precondition is satisfied.
 24. Acomputer readable medium having stored thereon instructions which, whenexecuted by a processor, cause the processor to perform the steps of:(a) receive from each of a plurality of bidders at least one bidcomprised of at least one item, an initial quantity of each item, and aprice for all of the item(s) and their quantities; (b) determine anallocation that is optimal for the type of exchange being conducted,wherein said allocation includes a plurality of bids with each bid ofsaid allocation including all of the items of the bid and at least partof the initial quantity of each item; (c) display at least a portion ofeach bid of said allocation to each bidder of a first subset of thebidders that has at least one bid that is not included in saidallocation; (d) receive from each bidder of a subset of the first subsetof bidders at least one of a new bid and an amendment to an existing bidof the bidder; and (e) repeat steps (b)-(d) until a predeterminedcondition is satisfied.
 25. The computer readable medium of claim 24,wherein each item includes one of a tangible good, a service and money.26. The computer readable medium of claim 24, wherein the predeterminedcondition includes at least one of (i) a lapse of a predetermined timeinterval from commencement of the exchange, (ii) a manual abort, and(iii) a sum of the prices of the bids of the allocation reaching apredetermined value.
 27. The computer readable medium of claim 24,wherein: each bid of a subset of the bids has associated therewith anexchange description data (EDD) established by the bidder of said bid(bidder EDD); bidder EDD comprises at least one rule (or constraint) forprocessing at least one of (i) a bid, (ii) at least one item of a bid,and (iii) a subset of bids that includes all or less than all of thebids when determining the allocation; and step (b) further includesdetermining the allocation as a function of bidder EDD.
 28. The computerreadable medium of claim 27, wherein bidder EDD includes at least onerule related to: bid attribute(s), bid adjustment(s), item attribute(s),item adjustment(s), free disposal, action, cost constraint/requirement,unit constraint/requirement, counting constraint/requirement,homogeneity constraint, mixture constraint, cost/unit condition pricing,quote request and reserve price(s).
 29. The computer readable medium ofclaim 27, wherein the portion of the at least one bid in step (c)includes at least one of: (i) the at least one item of the bid, (ii) thequantity of the at least one item of the bid, (iii) the price for all ofitem(s) and their quantities, and (iv) at least a portion of the bidderEDD.
 30. The computer readable medium of claim 24, wherein theinstructions further cause the processor to display a portion of atleast one bid that was determined to be part of the allocation to eachbidder of a second subset of bidders that has at least one bid that ispart of the allocation.
 31. The computer readable medium of claim 30,wherein: each subset of bidders includes (i) all or (ii) less than allof the plurality of bidders; and each subset of bids includes (i) all or(ii) less than all of the bids.
 32. The computer readable medium ofclaim 30, wherein the portion of the at least one bid in step (c)includes at least one of: (i) at least one item of the bid, (ii) theinitial or allocated quantity of at least one item of the bid, (iii) theprice for all of item(s) and their quantities, and (iv) at least aportion of the bidder EDD.
 33. The computer readable medium of claim 24,wherein the exchange is one of a forward auction and a reverse auction.34. The computer readable medium of claim 27, wherein the amendment tothe existing bid in step (d) includes at least one of: the addition ofat least one new rule to bidder EDD associated with the existing bid;the deletion of at least one rule from bidder EDD associated with theexisting bid; the amendment of a value associated with at least one ruleof bidder EDD associated with the existing bid; the amendment of a valueof the quantity of at least one item of the existing bid; and theamendment of the price for all of item(s) and their quantities.
 35. Thecomputer readable medium of claim 34, wherein the instructions furthercause the processor to impose at least one supervisory constraint thatlimits at least one of (i) adding at least one rule to a bidder EDD,(ii) deleting at least one rule from a bidder EDD, (iii) relaxing atleast one rule of a bidder EDD and (iv) tightening of at least one saidrule of a bidder EDD.
 36. The computer readable medium of claim 27,wherein the instructions further cause the processor to: determine theallocation step (b) based on EDD established by a bid taker (bid takerEDD); and receive from the bid taker step (d) at least one of a new bidtaker EDD and an amendment to an existing bid taker EDD of the bidtaker, wherein the amendment to the existing bid taker EDD of the bidtaker includes at least one of: the addition of at least one new rule tothe existing bid taker EDD; the deletion of at least one rule from theexisting bid taker EDD; and the amendment of a value associated with atleast one rule of the existing bid taker EDD.
 37. The computer readablemedium of claim 26, wherein the instructions further cause the processorto extend the predetermined time interval in response to receiving a bidthat improves the allocation within a predetermined duration of the endof the predetermined time interval.
 38. The computer readable medium ofclaim 37, wherein: in an exchange that includes plural bidders andplural bid takers, the allocation improves if (i) the number of itemsexchanged increases or (ii) a difference between a sum of the prices ofthe buy bids and a sum of the prices of the sell bids of the allocationincreases; in an exchange that includes a single buyer and pluralsellers (reverse auction), the allocation improves if a sum of theprices of the bids of the allocation decreases; and in an exchange thatincludes plural buyers and a single seller (forward auction), theallocation improves if a sum of the prices of the bids of the allocationincreases.
 39. The computer readable medium of claim 24, wherein theinstructions further cause the processor to: logically OR all thereceived bids; and logically XOR all bids received from one bidder thatinclude at least one item in common.
 40. The computer readable medium ofclaim 24, wherein the instructions further cause the processor to:determine the allocation in step (b) as a function of exchangedescription data (EDD) established by a bid taker (bid taker EDD),wherein bid taker EDD comprises at least one rule (or constraint) forprocessing at least one of (i) a bid, (ii) at least one item of a bid,and (iii) a subset of the plurality of the bids when determining theallocation; and receive from the bid taker in step (d) at least one ofnew EDD and an amendment to an existing EDD of the bid taker, whereinthe amendment to the existing EDD of the bid taker includes at least oneof: adding at least one new rule to the existing bid taker EDD; deletingat least one rule from the existing bid taker EDD; and amending a valueassociated with at least one rule of the existing bid taker EDD.
 41. Thecomputer readable medium of claim 40, wherein the instructions furthercause the processor to impose at least one supervisory constraint thatlimits at least one of (i) adding at least one rule to a bid taker EDD,(ii) deleting at least one rule from a bid taker EDD, (iii) relaxing atleast one rule of a bid taker EDD and (iv) tightening of at least onesaid rule of a bid taker EDD.
 42. The computer readable medium of claim40, wherein bid taker EDD includes at least one rule related to:objective(s), constraint relaxer(s), feasibility obtainer(s), bidadjustment(s), item attribute(s), item adjustment(s), free disposal,action, cost constraint/requirement, unit constraint/requirement,counting constraint/requirement, homogeneity constraint, mixtureconstraint, cost/unit condition pricing, quote request and reserveprice(s).
 43. The computer readable medium of claim 24, wherein theinstructions further cause the processor to cause an identification ofthe bidder of said bid to be displayed in step (c) .
 44. The computerreadable medium of claim 43, wherein the instructions further cause theprocessor to obscure the display of bidder identification.
 45. Thecomputer readable medium of claim 27, wherein at least one rule isintroduced into at least one bidder EDD in response to a bidderspecifying (i) a precondition of said rule and (ii) an effect to applyif said precondition is satisfied.
 46. The computer readable medium ofclaim 40, wherein at least one rule is introduced into at least one bidtaker EDD in response to a bid taker specifying (i) a precondition ofsaid rule and (ii) an effect to apply if said precondition is satisfied.47. The method of claim 22, wherein the bidder specifies theprecondition and the effect via a graphical user interface.
 48. Themethod of claim 23, wherein the bid taker specifies the precondition andthe effect via a graphical user interface.
 49. The method of claim 22,wherein the bidder specifies the precondition and the effect via agraphical user interface.
 50. The method of claim 22, wherein the bidtaker specifies the precondition and the effect via a graphical userinterface.